This paper proposes a self-calibrated sparse learning approach for estimating a sparse target vector, which is a …

, we also find mutual fund investors learn much more slowly than Bayes' rule. Mutual fund investors' slow learning is not … lack of sophistication, but is likely due to a low payoff from learning. Our results suggest learning speed depends on the …

Portfolio selection has attracted increasing attention in machine learning and AI communities recently. Portfolio … selection using on-line learning method has been extensively investigated previously. Literature about portfolio selection using … recurrent reinforcement learning (RRL) is relatively scarce and existing ones heavily rely on single asset trading system to …

This article aims to enhance factor investing with reinforcement learning (RL) techniques. The agent learns through …

This article aims to enhance factor investing with reinforcement learning (RL) techniques. The agent learns through …

We survey the recent literature on learning in financial markets. Our main theme is that many financial market … uncertain and subject to learning. We discuss phenomena related to the volatility and predictability of asset returns, stock …

We survey the recent literature on learning in financial markets. Our main theme is that many financial market … uncertain and subject to learning. We discuss phenomena related to the volatility and predictability of asset returns, stock …